26 to 50 of 1,773 Machine Learning Jobs in London

gain a competitive edge. Risk and Technology (Data Analytics): Develop data-driven solutions to help clients manage regulatory compliance, cybersecurity, and operational risks. Use advanced analytics, data visualisation, and machine learning techniques to provide clients with valuable insights that can inform risk management strategies. Assess and enhance the security of clients' technology infrastructure and support the design of … Google Cloud. You will also receive comprehensive training in areas like data analytics, cybersecurity, cloud computing, and business intelligence tools. These will be supported by practical, on-the-job learning and ongoing mentoring from experienced professionals at PwC. Additionally, you'll have the opportunity to gain exposure to emerging technologies, including: Artificial Intelligence (AI) Blockchain Robotic Process Automation (RPA … Internet of Things (IoT) Through a blend of structured learning, mentoring, and hands-on experience, you'll develop the skills necessary to advise clients on their technology strategies and implementation. Programme Highlights: Work across a variety of industries, including financial services, retail, healthcare, and more, providing technology-driven solutions. Collaborate with experienced technology consultants and risk management professionals to More ❯

includes guiding and mentoring fellow engineers, leading technical discussions, and making technical decisions and engage with key stakeholders in WWIT.The candidate must be open minded and interested in continuous learning, while being curious and unafraid to ask questions. He/She must be willing to innovate and initiate change, discover new solutions and present new ideas. He/She … Expertise on native AWS/Azure platforms including Serverless functions , preferably Lambda in AWS Passionate expert in Modern Engineering, DevOps practices - Strong understanding of CI/CD, AI/ML pipelines and automation tools. Prior experience in managing and integrating DevOps tools to streamline CI/CD pipelines, automate workflows, and enhance deployment efficiency Experience with containerization and orchestration technologies More ❯

Group. Job Title: Machine Learning Engineer Our Data Analytics business continues to grow and we are now looking for an experienced and technical Machine Learning (ML) Engineer to join one our offices with hybrid or remote UK working. This is an exciting role and would most likely suit someone with previous experience in a similar role … where they have gained knowledge and experience of designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. You must have good technical knowledge of Phyton, SQL, CI/CD and familiar with Power BI. A FTSE 250 company, they combine expertise and insight with advanced technology and analytics to address … members of the analytics team and non-technical stakeholders. Your profile Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting More ❯

Learning Scientist to join our Search & Ranking team in the UK. As part of the team you will work alongside a Product Manager, Backend Engineers and other ML Scientists playing a key role in building innovative models to power Depop’s search engine and ranking across the app. Responsibilities You will: Research, design and deliver ML solutions to … humble great teammate with an ability to work wimulti-functionalnal teams, including technical and non-technical stakeholders Passion for learning new skills and staying up-to-date with ML algorithms Bonus points Experience with Databricks and PySpark Experience with deep learning & large language models Experience with traditional, semantic, and hybrid search frameworks (e.g. Elasticsearch) Experience working with AWS … Quantum Chemistry and Machine Learning), London London, England, United Kingdom 3 weeks ago London Area, United Kingdom £80,000.00-£80,000.00 20 hours ago Senior AI/ML Engineer (Data Science & Software Focus) London, England, United Kingdom 23 hours ago Distinguished Research Scientist, Physics Informed AI London, England, United Kingdom 2 weeks ago London, England, United Kingdom More ❯

Machine Learning Scientist to join our Recommendations team in the UK. As part of the team you will work alongside a Product Manager, Backend Engineers and other ML Scientists playing a key role in building innovative models to power Depop’s search engine and ranking across the app. Responsibilities You will: Research, design and deliver ML solutions to … team player with an ability to work with cross-functional teams, including technical and non-technical stakeholders Passion for learning new skills and staying up-to-date with ML algorithms Bonus points Experience with Databricks and PySpark Experience with deep learning & large language models Experience with traditional, semantic, and hybrid search frameworks (e.g. Elasticsearch) Experience working with AWS … week ago London, England, United Kingdom 2 weeks ago Research Scientist (Quantum Chemistry and Machine Learning), London London, England, United Kingdom 4 days ago Senior AI/ML Engineer (Data Science & Software Focus) London, England, United Kingdom 5 days ago London, England, United Kingdom 2 months ago London Area, United Kingdom £80,000.00-£80,000.00 9 hours ago More ❯

Grow with us. We are looking for a Machine Learning Engineer to work along the end-to-end ML lifecycle, alongside our existing Product & Engineering team. About Trudenty: The Trudenty Trust Network provides personalised consumer fraud risk intelligence for fraud prevention across the commerce and payments ecosystem, starting with first-party and APP fraud prevention. We are at … have proven experience with data science and a track record of implementing fraud prevention, credit scoring or personalization algorithms. Setting up and maintaining real data pipelines to feed your ML models is light work for you, and you would have been as comfortable if this JD was for a ‘data engineer’. You have worked in a high growth and … data technologies like Apache Hadoop and Apache Spark. Familiarity with real-time data processing frameworks such as Apache Kafka or Flink. MLOps & Deployment: Experience deploying and maintaining large-scale ML inference pipelines into production environments. Proficiency with Docker for containerization and Kubernetes for orchestration. Familiarity with AWS cloud platform (experience with GCP or Azure is a plus). Experience monitoring More ❯

s AI Implementation Chapter is seeking a Machine Learning Engineer to be part of a team dedicated to building and supporting Generative AI, Machine Learning (ML) and Data Science solutions across the Fitch Ratings organization. This position could be based out of our Chicago, London, or Manchester offices. The AI Chapter’s team objectives: Implement AI … ML technology in collaboration with Fitch Ratings business partners and product squads Develop and support enterprise-level AI exploration tools and capabilities Provide guidance for efficient and secure development and deployment of AI Establish and maintain guidelines and processes for AI/ML governance How You’ll Make an Impact: Work closely with or as part of product squads to … build, integrate, and deploy AI and ML solutions, sharing best practices and learnings with other squad members. Effectively communicate data science & ML concepts to stakeholders, focusing on applicability to Fitch use cases Collaborate in developing and deploying ML & Gen AI solutions to meet enterprise goals and support innovation and experimentation. Collaborate with data scientists to identify innovative solutions that leverage More ❯

Advanced certifications in cloud technologies, security, or architecture are a plus. Nice to Have: Experience in highly regulated industries such as fintech, healthcare, or telecommunications. Knowledge of AI/ML platforms or other advanced analytics infrastructure. Familiarity with infrastructure-as-code (IaC) tools such as Terraform or CloudFormation. Experience with modern data engineering technologies (e.g., Kafka, Spark, Flink, etc.). More ❯

Senior Research Scientist (Foundational Research, Machine Learning) page is loaded Senior Research Scientist (Foundational Research, Machine Learning) Apply remote type Remote Job: Hybrid locations GBR-London-5 Canada Square time type Full time posted on Posted 30+ Days Ago job requisition id JREQ184676 Are you a curious and open-minded individual with an interest in state … in long-term research for the future. As a Senior Research Scientist, you will be part of a diverse global team of experts. We hire world-leading specialists in ML/NLP/GenAI, as well as Engineering, to drive the company's leading internal AI model development, fueled by an unprecedented wealth of data and powered by state-of … and exciting ways. About the Role In this opportunity, as Senior Research Scientist you will: Innovate : You will have the opportunity to try new and/or innovate new ML/NLP/IR/GenAI approaches and enjoy mentoring by world-leading experts. You will contribute ideas and work on solving real-world challenges using a wealth of data More ❯

us in shaping the future of intelligent testing through cutting-edge AI and model-driven engineering. Job responsibilities Serves as a subject matter expert on a wide range of ML techniques and optimizations. Provides in-depth knowledge of ML algorithms, frameworks, and techniques. Enhances ML workflows through advanced proficiency in large language models (LLMs) and related techniques. Conducts experiments using … latest ML technologies, analyzing results, tuning models Provides has Hands on coding to bring the experimental results into production solutions by collaborating with engineering team. Owning end to end code development in python for both proof of concept/experimentation and production-ready solutions. Optimizes system accuracy and performance by identifying and resolving inefficiencies and bottlenecks. Collaborates with product and … engineering teams to deliver tailored, science and technology-driven solutions. Integrates Generative AI within the ML Platform using state-of-the-art techniques. Required qualifications, capabilities, and skills Formal training or certification (MS and/or PhD) in Computer Science, Machine Learning, or a related field, with applied machine learning concepts experience. Experience in the Python More ❯

emphasise the importance of team spirit, cohesion, and appreciation - And through our talented people, innovative culture, and technical and business expertise, we deliver game changing outcomes every day. Our learning culture and flat hierarchy are our recipes for success. But don't take our word for it - Have a look at what our employees are saying: Hitachi Solutions: Recruiting … needs Provide expert advisory services to clients on AI best practices, ensuring delivery of scalable and efficient solutions. Define high-value business scenarios that can benefit from AI solutions (Machine Learning and Gen AI). Explore and analyse data from various sources and formats using tools such as Microsoft Fabric, Azure … Databricks, Azure Synapse Analytics, and Azure Machine Learning Implement data pipelines and workflows to automate and operationalize machine learning solutions using tools such as Azure ML Pipelines, Azure DevOps. Run experiments and monitor performance of machine learning solutions using tools such as Azure Azure ML, and Azure Application Insights. Operationalise and deploy AI solutions More ❯

S55 The AOP (Analytics Operations and Programs) team is responsible for creating core analytics, insight generation and science capabilities for ROW Ops. We develop scalable analytics applications, AI/ML products and research models to optimize operation processes. You will work with Product Managers, Data Engineers, Data Scientists, Research Scientists, Applied Scientists and Business Intelligence Engineers using rigorous quantitative approaches … As Data Scientist, you are able to use a range of science methodologies to solve challenging business problems when the solution is unclear. You will be responsible for building ML models to solve complex business problems and test them in production environment. The scope of role includes defining the charter for the project and proposing solutions which align with org … impact. You will achieve this by leveraging strong leadership and communication skills, data science skills and by acquiring domain knowledge pertaining to the delivery operations systems. You will provide ML thought leadership to technical and business leaders, and possess ability to think strategically about business, product, and technical challenges. You will also be expected to contribute to the science community More ❯

Deliver Scalable AI Solutions Define approaches to embed and scale machine learning models within customer data platforms and enterprise systems. Partner with engineers and developers to deploy ML algorithms that deliver tangible business value. Ensure the scalability and efficiency of AI solutions in real-world production environments. Consult and Guide with Impact Understand business requirements and support the … and provide data science leadership to senior client stakeholders. Contribute expertise to new sales and pre-sales initiatives as a subject matter expert. Consult on complex analyses and advanced ML techniques across industries and use cases. Build Best Practices and Reusable Assets Create reusable components, accelerators, and frameworks to address both current and future business needs. Shape data science strategy … experience in the following skills: Core Data Science & Machine Learning Strong professional experience in data science, machine learning, and business analytics Hands-on experience with ML techniques such as XGBoost, deep neural networks, and transformers Practical knowledge of ML libraries and frameworks such as Fastai, Keras, TensorFlow, PyTorch, and Scikit-learn Ability to research, understand, and More ❯

the opportunity to experiment with our data sets and contribute to core AI strategies at the heart of what we deliver. You will rely on a diverse AI/ML and software ecosystem to enhance our core enterprise products and leverage cutting edge AI tools and methods to build new products that serve our end users. You will be exposed … Because I Have... A Master's or Ph.D. degree in Computer Science, Machine Learning, Data Science, Artificial Intelligence, Statistics or related field 3+ years of experience in ML/AI engineering, or software engineering with expertise in NLP Experience with AI/ML infrastructure, distributed training and a track record of building and deploying ML systems at scale … Solid understanding of AI system design principles and experience with ML/AIOps tools and best practices for model lifecycle management Familiarity with modern NLP architectures, including transformer models and LLMs based applications in production A passion for learning about and contributing to running a large-scale cloud-native Machine Learning platform Extensive experience with programming languages More ❯

Neurolabs is looking for a talented Senior Machine Learning Engineer to join our team. As an ML Engineer at Neurolabs, you will be responsible for developing, implementing, and optimizing Computer Vision models that empower our retail automation solutions. Your expertise will play a crucial role in transforming images into structured data and driving product enhancements that meet our … and platform engineers, to deliver integrated Computer Vision solutions. Performance Monitoring: Monitor live models and performance metrics, troubleshoot issues, and implement updates as necessary to ensure optimal performance. Continuous Learning: Stay updated with the latest research and advances in machine learning and computer vision. Drive innovation by applying new techniques and methods to our projects. Educational Background … learning. Professional Experience: 5+ years of hands-on experience deploying Computer Vision models in production environments. Strong proficiency in Python. Experience with cloud environments (AWS, GCP) and tools for ML model deployment (Docker, Kubernetes, etc.). Technical Skills: In-depth understanding of computer vision techniques, including image classification, detection, and segmentation. Familiarity with Large Vision Models is a big plus. More ❯

chance to shape both models and how we think about fraud detection as a wider team Responsibilities: You will be part of a team that builds, evaluates and deploys machine learning models to improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions … and non-technical stakeholders Demonstrable experience deploying machine learning solutions in a production environment, and familiarity with version controls systems (e.g. Git) Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data … in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to quantify the level of fairness and bias machine learning models Enthusiasm for improving fraud detection systems and a proactive, problem-solving mindset Interview process Interviewing is a two way process and we want you to have the time and opportunity More ❯

chance to shape both models and how we think about fraud detection as a wider team Responsibilities: You will be part of a team that builds, evaluates and deploys machine learning models to improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions … and non-technical stakeholders Demonstrable experience deploying machine learning solutions in a production environment, and familiarity with version controls systems (e.g. Git) Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data … in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to quantify the level of fairness and bias machine learning models Enthusiasm for improving fraud detection systems and a proactive, problem-solving mindset Interview process Interviewing is a two way process and we want you to have the time and opportunity More ❯

Scientist to help improve the performance of our targeting and optimization products. The Applied Science team at Sojern develops services and pipelines to optimize advertising campaign performance and applies machine learning at scale for thousands … of customers. We utilize a range of algorithms and methods to do this including: Bayesian statistics and supervised learning to model conversion rates and revenue Scaled AI/ML with Tensorflow/Vertex AI to model a traveler’s propensity to book Time series forecasting As a part of the Science and Optimization team, we deliver through the full … this role requires availability to work later business hours, with a regular schedule ending at 7:00 PM Mon-Thu. What you will do: Design and maintain statistical and machine learning models to optimize campaign performance Model key performance advertising metrics like conversion rates and click through rates, and use those metrics to automate estimation of campaign bids More ❯

is ready to the design, development, and deployment of secure AI powered systems. You'll be at the heart of a diverse, multidisciplinary and fast paced team to integrate ML models into robust, mission ready software environments. you'll contribute to cross-disciplinary discussions, ensuring AI solutions align with business goals and operational needs. Your expertise will help close the … d love to hear from you. Responsibilities: Design and implement scalable backend services for AI model deployment in secure environments Collaborate with data scientists and defence analysts to productionise ML models (e.g., for threat detection, anomaly detection, autonomous systems, or decision support tools) Build and maintain secure APIs and infrastructure using Python (FastAPI/Flask), Docker, and Kubernetes Contribute to … DevSecOps workflows including automated testing, monitoring, and continuous integration Requirements: 3+ years of experience in software engineering, with a focus on AI/ML integration Proficiency in Python and ML frameworks such as PyTorch or TensorFlow Strong grasp of software architecture and microservices Experience working in containerised environments (Docker, Kubernetes) Familiarity with CI/CD pipelines, secure deployment practices and More ❯

AI solutions to solve complex business problems. Collaborate with cross-functional teams to gather requirements and translate them into technical specifications. Build and maintain production-grade Python applications for machine learning and AI. Apply statistical analysis and machine learning techniques to derive insights from large datasets. Develop natural language processing (NLP) models to enhance user experience … the Role, You Must Have As a Senior Data Scientist, you should have strong commercial development experience in developing and deploying LLM-based applications. Strong understanding of AI/ML algorithms, data science, and machine learning. Demonstrated proficiency in: Rapid prototyping of Data Science and Machine learning problems on large datasets. Building agentic workflows and autonomous agents More ❯

problems Champion a broad range of data products to ensure business impact (multi-channel marketing optimization, data foundation, knowledge management platform and others) Collaborate with team-members (software engineer, ML engineers, data engineers, product owners, etc.) in design reviews and critical feedback sessions to continuously improve product delivery Distil complex analytical findings into simple, understandable and effective messages. Use excellent … team and business stakeholders; effectively translate technical concepts to business stakeholders and vice versa. Proven experience of change management skills. Core technical skills: Strong knowledge of data science fundamentals (Machine Learning methods, Statistics). Fluent in common analytics tools (Python, Pandas, Numpy, ScikitLearn, SQL, etc.) Comfortable to use data visualization libraries (e.g. Seaborn, Matplotlib) Demonstrated initiative, judgment and … characteristics, it would be a plus: PhD - in a STEM subject and experience in related field i.e. Statistics, Data Science or equivalent experience (Mathematics, Statistics, Information Science, Computer Science, ML, AI, Bioinformatics or similar) Demonstrated experience in product ownership and stakeholder management. Demonstrated experience with Azure stack (databricks, AMLS, etc.) Knowledge of the data landscape in healthcare (EHR, claims data More ❯

required: Microsoft Certified: Azure Data Engineer Associate Microsoft Certified: Azure Data Scientist Associate Active Databricks Certifications: At least one of the following is required: Data Engineer Associate or Professional ML Engineer Associate or Professional Experience in designing and implementing data governance frameworks and data quality processes. Experience working with large datasets and complex data landscapes. Familiarity with economic data and … skills. Strong analytical and problem-solving skills. Experience with data visualisation tools (e.g., Tableau, Power BI). Experience with metadata management tools e.g. Purview. Knowledge of data science and machine learning concepts. Experience with API design and development. #J-18808-Ljbffr More ❯

and unstructured biological data that contribute to the evolution of BenchSci’s Knowledge Graph Integrate public life science data into the biological ontology in our Knowledge Graph Collaborate with ML, Data engineers, and Science to solve complex data mining and extraction challenges, enabling us to capture and model scientific experiments and results Seek out leadership opportunities and act as a … you will excel best if this environment suits you You have experience working in cross-functional teams with product managers, scientists, project managers, and engineers from other disciplines (e.g., machine learning) Outstanding verbal and written communication skills Can clearly explain complex technical concepts/systems to engineering peers and non-engineering stakeholders across teams Experience executing as part … vacation day every year Company closures for 14 more days throughout the year Flex time for sick days, personal days, and religious holidays Comprehensive health and dental benefits. Annual learning & development budget A one-time home office set-up budget to use upon joining BenchSci An annual lifestyle spending account allowance Generous parental leave benefits with a top-up More ❯

the likes of SQL, SSIS, Python, Java, Scala, XML/FpML and Power BI Data architecture, data lineage and all aspects of AI including, but not limited to, NLP, ML, deep learning and Generative AI Testing/quality engineering; experience of test automation will be beneficial Process Automation, BPM and Digital Platforms, e.g. Pega Cloud technology (knowledge of any … and Google would be beneficial) Experience of handling information security and privacy challenges Interest and awareness in emerging technologies Experience of vendor packages. An appreciation of Artificial Intelligence and Machine Learning Academic and prior experience A university degree, 2:1 (or equivalent) or above is usually preferred, however we would be open to outstanding candidates who may have More ❯

We are looking for a Senior Software Engineer to lead the design, development, and implementation of machine learning models, build scalable applications, and optimise workflows.Not only will you directly contribute to our client deliverables, but you will have the opportunity to experiment with a range of cutting-edge techniques and deliver full-stack data science projects, from solution … implementation of complex AI models and algorithms Define data collection, cleaning, and pre-processing strategies Architect and maintain robust data pipelines and data management systems Lead the training of machine learning models, ensuring high performance and scalability Build processes for extracting, cleaning and transforming data (SQL/Python) Optimize model parameters and architectures for maximum efficiency and accuracy … Ensure seamless integration of AI solutions with existing systems and applications Stay updated with the latest advancements in AI and machine learning Present findings to clients through written documentation, calls and presentations Be an example of software engineering best-practice e.g. Git/Docker/cloud deployment Contribute to proposals for exciting new data science opportunities Provide direction More ❯